384 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART C:APPLICATIONS AND REVIEWS, VOL. 40, NO. 4, JULY 2010 A Frequency-based Approach for Features Fusion in Fingerprint and Iris Multimodal Biometric Identification Systems Vincenzo Conti, Carmelo Militello, Filippo Sorbello, Member, IEEE, and Salvatore Vitabile, Member, IEEE Abstract—The basic aim of a biometric identification system is to discriminate automatically between subjects in a reliable and dependable way, according to a specific-target application. Mul- timodal biometric identification systems aim to fuse two or more physical or behavioral traits to provide optimal False Acceptance Rate (FAR) and False Rejection Rate (FRR), thus improving sys- tem accuracy and dependability. In this paper, an innovative multi- modal biometric identification system based on iris and fingerprint traits is proposed. The paper is a state-of-the-art advancement of multibiometrics, offering an innovative perspective on features fusion. In greater detail, a frequency-based approach results in a homogeneous biometric vector, integrating iris and fingerprint data. Successively, a hamming-distance-based matching algorithm deals with the unified homogenous biometric vector. The proposed multimodal system achieves interesting results with several com- monly used databases. For example, we have obtained an inter- esting working point with FAR = 0% and FRR = 5.71% using the entire fingerprint verification competition (FVC) 2002 DB2B database and a randomly extracted same-size subset of the BATH database. At the same time, considering the BATH database and the FVC2002 DB2A database, we have obtained a further interest- ing working point with FAR = 0% and FRR = 7.28% ÷ 9.7%. Index Terms—Fusion techniques, identification systems, iris and fingerprint biometry, multimodal biometric systems. I. INTRODUCTION I N AN ACTUAL technological scenario, where Information and Communication Technologies (ICT) provide advanced services, large-scale and heterogeneous computer systems need strong procedures to protect data and resources access from unauthorized users. Authentication procedures, based on the simple username–password approach, are insufficient to provide a suitable security level for the applications requiring a high level of protection for data and services. Biometric-based authentication systems represent a valid al- ternative to conventional approaches. Traditionally biometric Manuscript received May 29, 2009; revised November 20, 2009; accepted February 7, 2010. Date of publication April 22, 2010; date of current version June 16, 2010. This paper was recommended by Associate Editor E. R. Weippl. V. Conti, C. Militello, and F. Sorbello are with the Department of Com- puter Engineering, University of Palermo, Palermo 90128, Italy (e-mail: conti@unipa.it; militello@unipa.it; sorbello@unipa.it). S. Vitabile is with the Department of Biopathology, Medical and Foren- sic Biotechnologies, University of Palermo, Palermo 90127, Italy (e-mail: vitabile@unipa.it). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TSMCC.2010.2045374 systems, operating on a single biometric feature, have many limitations, which are as follows [1]. 1) Trouble with data sensors: Captured sensor data are often affected by noise due to the environmental conditions (in- sufficient light, powder, etc.) or due to user physiological and physical conditions (cold, cut fingers, etc). 2) Distinctiveness ability: Not all biometric features have the same distinctiveness degree (for example, hand- geometry-based biometric systems are less selective than the fingerprint-based ones). 3) Lack of universality: All biometric features are universal, but due to the wide variety and complexity of the human body, not everyone is endowed with the same physical features and might not contain all the biometric features, which a system might allow. Multimodal biometric systems are a recent approach devel- oped to overcome these problems. These systems demonstrate significant improvements over unimodal biometric systems, in terms of higher accuracy and high resistance to spoofing. There is a sizeable amount of literature that details differ- ent approaches for multimodal biometric systems, which have been proposed [1]–[4]. Multibiometrics data can be combined at different levels: fusion at data-sensor level, fusion at the feature- extraction level, fusion at the matching level, and fusion at the decision level. As pointed out in [5], features-level fusion is eas- ier to apply when the original characteristics are homogeneous because, in this way, a single resultant feature vector can be calculated. On the other hand, feature-level fusion is difficult to achieve because: 1) the relationship between the feature spaces could not be known; 2) the feature set of multiple modalities may be incompatible; and 3) the computational cost to process the resultant vector is too high. In this paper, a template-level fusion algorithm resulting in a unified biometric descriptor and integrating fingerprint and iris features is presented. Considering a limited number of meaning- ful descriptors for fingerprint and iris images, a frequency-based codifying approach results in a homogenous vector composed of fingerprint and iris information. Successively, the Hamming Distance (HD) between two vectors is used to obtain its simi- larity degree. To evaluate and compare the effectiveness of the proposed approach, different tests on the official fingerprint veri- fication competition (FVC) 2002 DB2 fingerprint database [30] and the University of Bath Iris Image Database (BATH) iris database [31] have been performed. In greater details, the test conducted on the FVC2002 DB2B database and a subset of the BATH database (ten users) have resulted in False Acceptance 1094-6977/$26.00 © 2010 IEEE